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Artificial Life and Robotics
Published in: Artificial Life and Robotics 1/2016

01-03-2016 | Original Article

Quaternionic multistate Hopfield neural network with extended projection rule

Authors: Toshifumi Minemoto, Teijiro Isokawa, Haruhiko Nishimura, Nobuyuki Matsui

Published in: Artificial Life and Robotics | Issue 1/2016

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Abstract

The aim of this paper is to investigate storing and recalling performances of embedded patterns on associative memory. The associative memory is composed of quaternionic multistate Hopfield neural network. The state of a neuron in the network is described by three kinds of discretized phase with fixed amplitude. These phases are set to discrete values with arbitrary divide size. Hebbian rule and projection rule are used for storing patterns to the network. Recalling performance is evaluated through storing random patterns with changing the divide size of the phases in a neuron. Color images are also embedded and their noise tolerance is explored.
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Metadata
Title
Quaternionic multistate Hopfield neural network with extended projection rule
Authors
Toshifumi Minemoto
Teijiro Isokawa
Haruhiko Nishimura
Nobuyuki Matsui
Publication date
01-03-2016
Publisher
Springer Japan
Published in
Artificial Life and Robotics / Issue 1/2016
Print ISSN: 1433-5298
Electronic ISSN: 1614-7456
DOI
https://doi.org/10.1007/s10015-015-0247-4

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